Abstract
The paper presents a simplified mathematical model of disctype transformer winding for frequency response analysis (FRA) based on traveling wave and multiconductor transmission line theories. The simplified model is applied to the FRA simulation of a transformer winding. In order to identify the distributed parameters of the model, an intelligent learning technique, rooted from particle swarm optimiser with passive congregation (PSOPC) is utilised. Simulations and discussions are presented to explore the proposed optimization approach.
| Original language | English |
|---|---|
| Title of host publication | Applications of Evolutionary Computing - EvoWorkshops 2007 |
| Subtitle of host publication | EvoCOMNET, EvoFIN, EvoIASP, EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTRANSLOG, Proceedings |
| Pages | 145-152 |
| Number of pages | 8 |
| Publication status | Published - Aug 27 2007 |
| Event | EvoWorkshops 2007: EvoCOMNET, EvoFIN, EvoIASP, EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTRANSLOG - Valencia, Spain Duration: Apr 11 2007 → Apr 13 2007 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 4448 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | EvoWorkshops 2007: EvoCOMNET, EvoFIN, EvoIASP, EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTRANSLOG |
|---|---|
| Country | Spain |
| City | Valencia |
| Period | 4/11/07 → 4/13/07 |
Keywords
- Particle swarm optimiser with passive congregation
- Transformer winding mathematical model
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
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Cite this
Shintemirov, A., Tang, W. H., Lu, Z., & Wu, Q. H. (2007). Simplified transformer winding modelling and parameter identification using particle swarm optimiser with passive congregation. In Applications of Evolutionary Computing - EvoWorkshops 2007: EvoCOMNET, EvoFIN, EvoIASP, EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTRANSLOG, Proceedings (pp. 145-152). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4448 LNCS).